Putting AI to Work

Deirdre Houchen
Senior Marketing Director, ERP/EPM, Oracle

Overblown claims for artificial intelligence (AI) have left many in business skeptical of its potential. But CFOs are learning just how powerful these new tools already are, says Dee Houchen.

Some researchers say development of artificial intelligence (AI) might stall as the limitations of the technologies become clearer. But if the skeptics looked at leading finance functions, they’d see AI already hard at work. Today’s connected systems generate huge amounts of data – that all flows through finance. And any place you find data-driven processes, you’ll find AI solutions to help.

So where should you look for an AI advantage?

By breaking down the gains into three core areas: efficiency, insight and influence.

Robotic process automation (RPA) is a great example of the efficiency angle. But “touchless” transactions – intelligently merging purchase orders, goods receivables and invoices – are just the start. Oracle is working with businesses on recommended user actions, intelligent document reconciliation, automated audit, close orchestration and compliance.

AI works best with large data-sets, and it’s here that its insight capabilities become clear. At both ends of the supply chain, smarter analysis can optimize stock, logistics, payments, pricing and more based on high volumes of internal, supplier and customer data. 

Influence takes us to a higher level, applying AI to build out continuous close and smarter exception monitoring, for example, allowing finance to describe the business in new ways, creating opportunities to see whole new business models. 

Oracle works with businesses using our Adaptive Intelligent applications to deliver these gains – with AI, that’s baked into the core of the application, not bolted on as an afterthought.

Imagine if your finance function could support real-time supplier performance measurement and dynamically adjust discount rates, scheduling payment terms to match day-to-day working capital requirements.

Using more sources of data, especially through leveraging the power of the cloud, to build out better solutions also helps break down silos between finance, marketing, operations and other functions. “With machine learning we are able to use credit analytics in a very different way,” says Tina Singh, chief digital officer at Mahindra Finance. “By combining new credit models with data on cost of customer acquisition, and on customer behavior and their mobility patterns, our marketing function can target customers more effectively.”

As powerful new technologies such as artificial intelligence, machine learning and intelligent automation become mainstream, we are starting to grasp their potential for transforming how we work and create value. Over the last decade, productivity growth globally has slowed across all sectors, but CFOs can lead the next wave of prosperity, creating intelligent finance functions able to effectively seize the opportunities created by these technologies and best practices they continuously deliver.

Explore the productivity data, compiled by the OECD, for your country, in our interactive infographic.

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